Items related to Anomaly Detection Principles and Algorithms (Terrorism,...
Synopsis
This book provides a readable and elegant presentation of the principles of anomaly detection,providing an easy introduction for newcomers to the field. A large number of algorithms are succinctly described, along with a presentation of their strengths and weaknesses.
The authors also cover algorithms that address different kinds of problems of interest with single and multiple time series data and multi-dimensional data. New ensemble anomaly detection algorithms are described, utilizing the benefits provided by diverse algorithms, each of which work well on some kinds of data.
With advancements in technology and the extensive use of the internet as a medium for communications and commerce, there has been a tremendous increase in the threats faced by individuals and organizations from attackers and criminal entities. Variations in the observable behaviors of individuals (from others and from their own past behaviors) have been found to be useful in predicting potential problems of various kinds. Hence computer scientists and statisticians have been conducting research on automatically identifying anomalies in large datasets.
This book will primarily target practitioners and researchers who are newcomers to the area of modern anomaly detection techniques. Advanced-level students in computer science will also find this book helpful with their studies.
"synopsis" may belong to another edition of this title.
Review
“This book presents the interesting topic of anomaly detection for a very broad audience. ... The presentation is really useful: for each technique, some motivation is given, including real-life situations, a comprehensible formalization, and pros and cons, which gives readers an idea of how useful the technique will be in practice. ... Probably the most important contribution of the book is its citations and references for further reading, which may help casual readers better understand each technique ... .” (Santiago Escobar, Computing Reviews, January, 2019)
"About this title" may belong to another edition of this title.
- PublisherSpringer
- Publication date2018
- ISBN 10 3319675249
- ISBN 13 9783319675244
- BindingHardcover
- LanguageEnglish
- Edition number1
- Number of pages239
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Anomaly Detection and Security Applications
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Springer International Publishing, 2018
ISBN 10: 3319675249
ISBN 13: 9783319675244
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents new algorithms for static and time series datasetsIntroduces new ensemble methods for improved anomaly detectionCovers rank-based anomaly detection algorithmsDiscusses the pros and cons of various approaches used for anomaly. Seller Inventory # 158491530
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Anomaly Detection Principles and Algorithms
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Springer International Publishing Jan 2018, 2018
ISBN 10: 3319675249
ISBN 13: 9783319675244
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Hardcover
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
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Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book provides a readable and elegant presentation of the principles of anomaly detection,providing an easy introduction for newcomers to the field. A large numberof algorithms are succinctly described, along with a presentation of theirstrengths and weaknesses.The authors also cover algorithms that addressdifferent kinds of problems of interest with single and multiple time seriesdata and multi-dimensional data. New ensemble anomaly detectionalgorithms are described, utilizing the benefits provided by diversealgorithms, each of which work well on some kinds of data.With advancements in technology and the extensive use of the internet asa medium for communications and commerce, there has been atremendous increase in the threats faced by individuals and organizationsfrom attackers and criminal entities. Variations in the observable behaviorsof individuals (from others and from their own past behaviors) have beenfound to be useful in predicting potential problems of various kinds. Hencecomputer scientists and statisticians have been conducting research on automatically identifying anomalies in large datasets. This book will primarily target practitioners and researchers who are newcomers to the area of modern anomaly detection techniques. Advanced-level students in computer science will also find this book helpful with their studies. 240 pp. Englisch. Seller Inventory # 9783319675244
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